Open AccessElastic FWI Without Low Frequencies Based on n-th Power Operation and Convolved Wavefields
Author(s) -
Pan Zhang,
Liguo Han,
Jianhui Zhao,
Yuchen Yin
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/660/1/012045
Subject(s) - inversion (geology) , frequency domain , computer science , algorithm , wavelet , time domain , waveform , geology , seismology , telecommunications , artificial intelligence , computer vision , tectonics , radar
The elastic full-waveform inversion (FWI) can use the recorded multi-component seismic data to construct high-precision multi-parameter models of the subsurface media such as P- and S-wave velocity models. However, due to the reasons such as data quality and algorithm limitations, there are still many problems in the promotion and application of elastic FWI method. Aiming at alleviating the influence of low-frequency data absence on the inversion results, we propose a robust elastic FWI method based on the n-th power operation. The n-th power of the seismic data can compress the time-domain waveform and expand its frequency-band. The FWI objective function constructed using the n-th power wavefields shows better convexity. By successively lowering the power during the inversion, we can realize a new multiscale FWI strategy, which is also a data-domain layer-stripping strategy. Seismic data will be more sensitive to the source wavelet errors after the n-th power operation. To mitigate this problem, we propose a robust objective function for elastic FWI using the n-th power operation and the convolved wavefields. Finally, the validity of the method is verified by numerical examples.